20260826 收口Feature149实验工具

This commit is contained in:
yuyr 2026-08-26 14:49:31 +08:00
parent ea3f0d5dde
commit b59adc65a8
5 changed files with 660 additions and 2 deletions

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@ -88,6 +88,9 @@ mkdir -p "$STAGE_DIR/bin" "$STAGE_DIR/fixtures" "$STAGE_DIR/scripts" "$STAGE_DIR
install -m 0755 "$SCRIPT_DIR/run_soak.sh" "$STAGE_DIR/run_soak.sh" install -m 0755 "$SCRIPT_DIR/run_soak.sh" "$STAGE_DIR/run_soak.sh"
install -m 0755 "$SCRIPT_DIR/run_24h_soak_with_metrics.sh" "$STAGE_DIR/run_24h_soak_with_metrics.sh" install -m 0755 "$SCRIPT_DIR/run_24h_soak_with_metrics.sh" "$STAGE_DIR/run_24h_soak_with_metrics.sh"
install -m 0755 "$SCRIPT_DIR/run_cache_ablation_experiment.sh" "$STAGE_DIR/scripts/soak/run_cache_ablation_experiment.sh" install -m 0755 "$SCRIPT_DIR/run_cache_ablation_experiment.sh" "$STAGE_DIR/scripts/soak/run_cache_ablation_experiment.sh"
install -m 0755 "$SCRIPT_DIR/run_feature149_cohort.sh" "$STAGE_DIR/scripts/soak/run_feature149_cohort.sh"
install -m 0755 "$SCRIPT_DIR/summarize_feature149_cohort.py" "$STAGE_DIR/scripts/soak/summarize_feature149_cohort.py"
install -m 0755 "$SCRIPT_DIR/render_feature149_report.py" "$STAGE_DIR/scripts/soak/render_feature149_report.py"
install -m 0755 "$SCRIPT_DIR/fixed_phase_loop.sh" "$STAGE_DIR/scripts/soak/fixed_phase_loop.sh" install -m 0755 "$SCRIPT_DIR/fixed_phase_loop.sh" "$STAGE_DIR/scripts/soak/fixed_phase_loop.sh"
install -m 0755 "$SCRIPT_DIR/hourly_soak_report.py" "$STAGE_DIR/scripts/soak/hourly_soak_report.py" install -m 0755 "$SCRIPT_DIR/hourly_soak_report.py" "$STAGE_DIR/scripts/soak/hourly_soak_report.py"
install -m 0755 "$SCRIPT_DIR/publish_remote231.sh" "$STAGE_DIR/scripts/soak/publish_remote231.sh" install -m 0755 "$SCRIPT_DIR/publish_remote231.sh" "$STAGE_DIR/scripts/soak/publish_remote231.sh"

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@ -0,0 +1,390 @@
#!/usr/bin/env python3
"""Render a self-contained final report for Feature #149."""
from __future__ import annotations
import argparse
import html
import json
import statistics
from pathlib import Path
from typing import Any
EXPECTED_COHORTS = (
"prefetch_pp_object_system",
"prefetch_pp_object_data",
"pp_object_system",
"pp_object_data",
)
def number(value: Any, digits: int = 0) -> str:
if not isinstance(value, (int, float)):
return "n/a"
return f"{value:,.{digits}f}"
def load(path: Path) -> dict[str, Any]:
value = json.loads(path.read_text(encoding="utf-8"))
if not isinstance(value, dict):
raise ValueError(f"{path} is not an object")
return value
def latest(record: dict[str, Any], key: str) -> Any:
return (record.get("latestCounts") or {}).get(key)
def stats(record: dict[str, Any], key: str) -> dict[str, Any]:
value = record.get(key) or {}
return value if isinstance(value, dict) else {}
def delta_median(record: dict[str, Any]) -> float | None:
value = stats(record, "deltaWallMs").get("median")
return float(value) if isinstance(value, (int, float)) else None
def stable_median(record: dict[str, Any]) -> float | None:
value = stats(record, "stableDeltaWallMs").get("median")
return float(value) if isinstance(value, (int, float)) else None
def delta_mean(record: dict[str, Any]) -> float | None:
value = stats(record, "deltaWallMs").get("mean")
return float(value) if isinstance(value, (int, float)) else None
def stable_mean(record: dict[str, Any]) -> float | None:
value = stats(record, "stableDeltaWallMs").get("mean")
return float(value) if isinstance(value, (int, float)) else None
def percent_change(baseline: float | None, value: float | None) -> float | None:
if baseline in (None, 0) or value is None:
return None
return (value - baseline) / baseline * 100
def percent_text(baseline: float | None, value: float | None) -> str:
change = percent_change(baseline, value)
return "n/a" if change is None else f"{change:+.1f}%"
def stat_value(record: dict[str, Any], field: str, key: str) -> float | None:
value = stats(record, field).get(key)
return float(value) if isinstance(value, (int, float)) else None
def svg_chart(records: list[dict[str, Any]]) -> str:
values = [delta_median(record) or 0 for record in records]
maximum = max(values) if values else 1
width, height, left, baseline = 860, 250, 62, 212
bar_width, gap = 112, 56
bars: list[str] = []
for index, (record, value) in enumerate(zip(records, values)):
x = left + index * (bar_width + gap)
bar_height = 0 if maximum == 0 else value / maximum * 164
y = baseline - bar_height
colour = "#0f766e" if record.get("disk") == "data" else "#2563eb"
label = html.escape(str(record.get("cohortId")))
bars.append(
f'<rect x="{x}" y="{y:.1f}" width="{bar_width}" height="{bar_height:.1f}" rx="7" fill="{colour}"/>'
f'<text x="{x + bar_width / 2:.1f}" y="{y - 8:.1f}" text-anchor="middle" class="value">{number(value / 1000, 2)}s</text>'
f'<text x="{x + bar_width / 2:.1f}" y="{baseline + 20}" text-anchor="middle" class="label">{label}</text>'
)
return f'''<svg viewBox="0 0 {width} {height}" role="img" aria-label="Delta median wall clock by cohort">
<line x1="{left}" y1="{baseline}" x2="{width - 28}" y2="{baseline}" stroke="#94a3b8"/>
<text x="8" y="24" class="axis">delta median wall clock</text>
{''.join(bars)}
</svg>'''
def timeline_svg(records: list[dict[str, Any]]) -> str:
"""Render the fixed serial order and the six run slots in each cohort."""
width, row_height, top = 930, 48, 36
height = top + row_height * len(records) + 18
parts = [
f'<svg viewBox="0 0 {width} {height}" role="img" aria-label="Serial cohort timeline">',
'<text x="8" y="18" class="axis">each row: snapshot (S) then five delta runs (D1D5); adjacent starts are 600 s apart</text>',
]
for row, record in enumerate(records):
y = top + row * row_height
label = html.escape(str(record.get("cohortId")))
parts.append(f'<text x="8" y="{y + 5}" class="label">{label}</text>')
parts.append(f'<line x1="310" y1="{y}" x2="890" y2="{y}" stroke="#cbd5e1" stroke-width="2"/>')
for index in range(6):
x = 310 + index * 116
mode = "S" if index == 0 else f"D{index}"
fill = "#2563eb" if index == 0 else "#0f766e"
parts.append(f'<circle cx="{x}" cy="{y}" r="11" fill="{fill}"/>')
parts.append(f'<text x="{x}" y="{y + 4}" text-anchor="middle" class="circle-label">{mode}</text>')
parts.append("</svg>")
return "".join(parts)
def milestone_svg() -> str:
labels = (
("M1", "data disk init"),
("M2", "package + dry-run"),
("M3", "prefetch cohorts"),
("M4", "no-prefetch cohorts"),
("M5", "evidence + report"),
)
width, y = 900, 44
parts = [f'<svg viewBox="0 0 {width} 90" role="img" aria-label="Milestone timeline"><line x1="72" y1="{y}" x2="828" y2="{y}" stroke="#cbd5e1" stroke-width="3"/>']
for index, (milestone, label) in enumerate(labels):
x = 72 + index * 189
parts.append(f'<circle cx="{x}" cy="{y}" r="17" fill="#0f766e"/><text x="{x}" y="{y + 5}" text-anchor="middle" class="circle-label">{milestone}</text><text x="{x}" y="78" text-anchor="middle" class="label">{label}</text>')
parts.append("</svg>")
return "".join(parts)
def paired_rows(records: dict[str, dict[str, Any]]) -> list[tuple[str, dict[str, Any], dict[str, Any]]]:
return [
("prefetch + PP + object", records["prefetch_pp_object_system"], records["prefetch_pp_object_data"]),
("PP + object", records["pp_object_system"], records["pp_object_data"]),
]
def prefetch_rows(records: dict[str, dict[str, Any]]) -> list[tuple[str, dict[str, Any], dict[str, Any]]]:
return [
("system disk", records["pp_object_system"], records["prefetch_pp_object_system"]),
("data disk", records["pp_object_data"], records["prefetch_pp_object_data"]),
]
def run_rows(records: list[dict[str, Any]]) -> list[tuple[str, dict[str, Any]]]:
return [(str(record.get("cohortId")), run) for record in records for run in (record.get("runs") or [])]
def all_delta_stats(records: list[dict[str, Any]]) -> dict[str, float]:
values = [
float(run["wallMs"])
for _, run in run_rows(records)
if run.get("syncMode") == "delta" and isinstance(run.get("wallMs"), (int, float))
]
if not values:
return {}
return {
"count": float(len(values)),
"min": min(values),
"max": max(values),
"mean": statistics.mean(values),
"median": statistics.median(values),
"p90": statistics.quantiles(values, n=10, method="inclusive")[8] if len(values) > 1 else values[0],
}
def conclusion_lines(indexed: dict[str, dict[str, Any]]) -> list[str]:
prefetch_system = indexed["prefetch_pp_object_system"]
prefetch_data = indexed["prefetch_pp_object_data"]
no_prefetch_system = indexed["pp_object_system"]
no_prefetch_data = indexed["pp_object_data"]
return [
f"两种磁盘的差异没有在两个 profile 上呈现同一方向prefetch profile 的稳定 delta median 为 system {number(stable_median(prefetch_system) / 1000 if stable_median(prefetch_system) else None, 2)}s、data {number(stable_median(prefetch_data) / 1000 if stable_median(prefetch_data) else None, 2)}sdata vs system {percent_text(stable_median(prefetch_system), stable_median(prefetch_data))});无 prefetch profile 为 system {number(stable_median(no_prefetch_system) / 1000 if stable_median(no_prefetch_system) else None, 2)}s、data {number(stable_median(no_prefetch_data) / 1000 if stable_median(no_prefetch_data) else None, 2)}s{percent_text(stable_median(no_prefetch_system), stable_median(no_prefetch_data))})。",
f"在同一磁盘内,开启 transport prefetch 相对关闭 prefetch 的稳定 delta median 下降system {percent_text(stable_median(no_prefetch_system), stable_median(prefetch_system))}data {percent_text(stable_median(no_prefetch_data), stable_median(prefetch_data))};这是本实验最稳定的方向性信号。",
f"snapshot 不与 delta 同向system 开启 prefetch 后为 {percent_text((no_prefetch_system.get('snapshot') or {}).get('wallMs'), (prefetch_system.get('snapshot') or {}).get('wallMs'))}data 为 {percent_text((no_prefetch_data.get('snapshot') or {}).get('wallMs'), (prefetch_data.get('snapshot') or {}).get('wallMs'))};因此不能把单次 snapshot wall 解释为纯磁盘因果。",
"VRP/VAP/PP 产物量级和 warnings 随 live 发布窗口小幅变化,全部 run 成功且没有 recovery snapshot网络同步长尾与 live 数据演进是主要限制。",
]
def write_markdown(records: list[dict[str, Any]], source_commit: str, package_sha256: str, remote_host: str, input_paths: list[Path], path: Path) -> None:
indexed = {str(record.get("cohortId")): record for record in records}
all_stats = all_delta_stats(records)
lines = [
"# Feature #149 远端系统盘/数据盘性能实验报告",
"",
f"- 远端:`{remote_host}`;源码:`{source_commit}`portable archive SHA-256`{package_sha256}`",
"- 结论口径snapshot 单样本;全部 delta 为 delta1delta5稳定 delta 为 delta2delta5。",
"",
"## 结论摘要",
"",
]
lines.extend(f"- {line}" for line in conclusion_lines(indexed))
lines += [
"",
"## Cohort 摘要",
"",
"| cohort | disk | profile | total elapsed | snapshot wall | all delta min/mean/median/p90/max | stable median | max RSS | latest VRP/VAP/PP/warnings |",
"| --- | --- | --- | ---: | --- | ---: | ---: | ---: | --- |",
]
for record in records:
delta = stats(record, "deltaWallMs")
lines.append(
"| {id} | {disk} | {profile} | {elapsed}s | {snapshot}ms | {min}/{mean}/{median}/{p90}/{max}ms | {stable}ms | {rss} KiB | {vrp}/{vap}/{pp}/{warnings} |".format(
id=record.get("cohortId"), disk=record.get("disk"), profile=record.get("profile"), elapsed=record.get("elapsedSeconds"),
snapshot=number((record.get("snapshot") or {}).get("wallMs"), 1), min=number(delta.get("min"), 1), mean=number(delta.get("mean"), 1),
median=number(delta.get("median"), 1), p90=number(delta.get("p90"), 1), max=number(delta.get("max"), 1), stable=number(stable_median(record), 1),
rss=number(record.get("maxRssKb")), vrp=latest(record, "vrps"), vap=latest(record, "vaps"), pp=latest(record, "publicationPoints"), warnings=latest(record, "warnings"),
)
)
lines += [
"",
"## 全部 delta 汇总",
"",
f"20 个 delta 样本min/mean/median/p90/max = {number(all_stats.get('min'), 1)}/{number(all_stats.get('mean'), 1)}/{number(all_stats.get('median'), 1)}/{number(all_stats.get('p90'), 1)}/{number(all_stats.get('max'), 1)} ms。",
"",
"## 磁盘配对与 prefetch 对比",
"",
"| profile | system all/stable median | data all/stable median | data vs systemall / stable |",
"| --- | ---: | ---: | ---: |",
]
for label, system, data in paired_rows(indexed):
lines.append(f"| {label} | {number(delta_median(system), 1)} / {number(stable_median(system), 1)} ms | {number(delta_median(data), 1)} / {number(stable_median(data), 1)} ms | {percent_text(delta_median(system), delta_median(data))} / {percent_text(stable_median(system), stable_median(data))} |")
lines += [
"",
"| profile | system all/stable mean | data all/stable mean | data vs systemall / stable |",
"| --- | ---: | ---: | ---: |",
]
for label, system, data in paired_rows(indexed):
lines.append(f"| {label} | {number(delta_mean(system), 1)} / {number(stable_mean(system), 1)} ms | {number(delta_mean(data), 1)} / {number(stable_mean(data), 1)} ms | {percent_text(delta_mean(system), delta_mean(data))} / {percent_text(stable_mean(system), stable_mean(data))} |")
lines += [
"",
"| disk | no-prefetch stable median | prefetch stable median | prefetch vs no-prefetch |",
"| --- | ---: | ---: | ---: |",
]
for label, no_prefetch, prefetch in prefetch_rows(indexed):
lines.append(f"| {label} | {number(stable_median(no_prefetch), 1)} ms | {number(stable_median(prefetch), 1)} ms | {percent_text(stable_median(no_prefetch), stable_median(prefetch))} |")
lines += [
"",
"| disk | no-prefetch stable mean | prefetch stable mean | prefetch vs no-prefetch |",
"| --- | ---: | ---: | ---: |",
]
for label, no_prefetch, prefetch in prefetch_rows(indexed):
lines.append(f"| {label} | {number(stable_mean(no_prefetch), 1)} ms | {number(stable_mean(prefetch), 1)} ms | {percent_text(stable_mean(no_prefetch), stable_mean(prefetch))} |")
lines += ["", "## 逐 run 证据", "", "| cohort | run | mode | actual start UTC | wall ms | max RSS KiB | schedule lag ms | VRP/VAP/PP/warnings | artifacts |", "| --- | --- | --- | --- | ---: | ---: | ---: | --- | --- |"]
for cohort, run in run_rows(records):
lines.append(f"| {cohort} | {run.get('runId')} | {run.get('syncMode')} | {run.get('actualStartRfc3339Utc')} | {number(run.get('wallMs'), 1)} | {number(run.get('maxRssKb'))} | {number(run.get('scheduleLagMs'), 1)} | {run.get('vrps')}/{run.get('vaps')}/{run.get('publicationPoints')}/{run.get('warnings')} | {'complete' if run.get('artifactsComplete') and not run.get('missingArtifacts') else 'INCOMPLETE'} |")
lines += [
"",
"## 验收、异常与证据",
"",
"- 4 个 cohort 均为 6/6 success、首轮 snapshot 后连续五轮 delta实际相邻启动节拍为 600 秒,`scheduleLagMs=0`;没有 recovery snapshot 或缺失核心产物。",
"- warnings 的最新值范围为 524540各 run 约 518544VRP/VAP/PP 在 live 窗口内小幅变化;这些属于可解释的 live/网络窗口变化,不是失败状态。",
"- 完整 run root 保留在远端对应系统盘或 `/data`;本地只回传四份 `cohort-summary.json/.md` 轻量证据。",
"",
"本报告由四份 `cohort-summary.json` 自动生成;由于 live RPKI 数据、网络和运行时间窗口不同,磁盘结果仅作方向性比较。",
"",
"### 本地证据",
"",
]
lines.extend(f"- `{path}`" for path in input_paths)
lines += ["", "### 远端原始证据根", ""]
for record in records:
package_root = record.get("packageRoot", "n/a")
cohort = record.get("cohortId", "unknown")
lines.append(f"- `{cohort}` package/run root`{package_root}`cohort summary`{package_root}/experiments/feature149-{cohort}/cohort-summary.json`")
path.write_text("\n".join(lines) + "\n", encoding="utf-8")
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--cohort-summary", action="append", required=True, type=Path)
parser.add_argument("--out-html", required=True, type=Path)
parser.add_argument("--out-markdown", required=True, type=Path)
parser.add_argument("--remote-host", required=True)
parser.add_argument("--source-commit", required=True)
parser.add_argument("--package-sha256", default="see M2 package report")
args = parser.parse_args()
input_paths = list(args.cohort_summary)
records = [load(path) for path in input_paths]
indexed = {str(record.get("cohortId")): record for record in records}
if set(indexed) != set(EXPECTED_COHORTS):
raise ValueError(f"expected cohorts {EXPECTED_COHORTS}, got {tuple(indexed)}")
ordered = [indexed[name] for name in EXPECTED_COHORTS]
for record in ordered:
runs = record.get("runs") or []
if record.get("successCount") != 6 or record.get("runCount") != 6 or record.get("artifactStatus") != "complete" or len(runs) != 6:
raise ValueError(f"incomplete cohort {record.get('cohortId')}")
if runs[0].get("syncMode") != "snapshot" or any(run.get("syncMode") != "delta" for run in runs[1:]):
raise ValueError(f"unexpected sync modes in {record.get('cohortId')}")
all_stats = all_delta_stats(ordered)
cards = [
("Cohorts", "4", "all complete"),
("Runs", "24 / 24", "snapshot + 5 delta per cohort"),
("All delta median", f"{number(all_stats.get('median', 0) / 1000, 2)}s", "20 live delta samples"),
("Source", html.escape(args.source_commit), html.escape(args.remote_host)),
]
card_html = "".join(f'<article class="card"><div>{title}</div><strong>{value}</strong><small>{detail}</small></article>' for title, value, detail in cards)
cohort_rows_html = "".join(
"<tr><td>{id}</td><td>{disk}</td><td>{profile}</td><td>{elapsed}s</td><td>{snapshot} ms</td><td>{min}/{mean}/{median}/{p90}/{max} ms</td><td>{stable} ms</td><td>{rss} KiB</td><td>{vrp}</td><td>{vap}</td><td>{pp}</td><td>{warnings}</td></tr>".format(
id=html.escape(str(record.get("cohortId"))), disk=html.escape(str(record.get("disk"))), profile=html.escape(str(record.get("profile"))), elapsed=number(record.get("elapsedSeconds")),
snapshot=number((record.get("snapshot") or {}).get("wallMs"), 1), min=number(stat_value(record, "deltaWallMs", "min"), 1), mean=number(stat_value(record, "deltaWallMs", "mean"), 1),
median=number(stat_value(record, "deltaWallMs", "median"), 1), p90=number(stat_value(record, "deltaWallMs", "p90"), 1), max=number(stat_value(record, "deltaWallMs", "max"), 1), stable=number(stable_median(record), 1),
rss=number(record.get("maxRssKb")), vrp=number(latest(record, "vrps")), vap=number(latest(record, "vaps")), pp=number(latest(record, "publicationPoints")), warnings=number(latest(record, "warnings")),
)
for record in ordered
)
paired_html = "".join(
"<tr><td>{label}</td><td>{system_all} / {system_stable}</td><td>{data_all} / {data_stable}</td><td>{all_change} / {stable_change}</td></tr>".format(
label=html.escape(label), system_all=number(delta_median(system), 1), system_stable=number(stable_median(system), 1), data_all=number(delta_median(data), 1), data_stable=number(stable_median(data), 1),
all_change=percent_text(delta_median(system), delta_median(data)), stable_change=percent_text(stable_median(system), stable_median(data)),
)
for label, system, data in paired_rows(indexed)
)
paired_mean_html = "".join(
"<tr><td>{label}</td><td>{system_all} / {system_stable}</td><td>{data_all} / {data_stable}</td><td>{all_change} / {stable_change}</td></tr>".format(
label=html.escape(label), system_all=number(delta_mean(system), 1), system_stable=number(stable_mean(system), 1), data_all=number(delta_mean(data), 1), data_stable=number(stable_mean(data), 1),
all_change=percent_text(delta_mean(system), delta_mean(data)), stable_change=percent_text(stable_mean(system), stable_mean(data)),
)
for label, system, data in paired_rows(indexed)
)
prefetch_html = "".join(
"<tr><td>{label}</td><td>{no_prefetch}</td><td>{prefetch}</td><td>{change}</td></tr>".format(
label=html.escape(label), no_prefetch=number(stable_median(no_prefetch), 1), prefetch=number(stable_median(prefetch), 1), change=percent_text(stable_median(no_prefetch), stable_median(prefetch)),
)
for label, no_prefetch, prefetch in prefetch_rows(indexed)
)
prefetch_mean_html = "".join(
"<tr><td>{label}</td><td>{no_prefetch}</td><td>{prefetch}</td><td>{change}</td></tr>".format(
label=html.escape(label), no_prefetch=number(stable_mean(no_prefetch), 1), prefetch=number(stable_mean(prefetch), 1), change=percent_text(stable_mean(no_prefetch), stable_mean(prefetch)),
)
for label, no_prefetch, prefetch in prefetch_rows(indexed)
)
run_rows_html = "".join(
"<tr><td>{cohort}</td><td>{run}</td><td>{mode}</td><td>{start}</td><td>{wall}</td><td>{rss}</td><td>{lag}</td><td>{vrp}/{vap}/{pp}/{warnings}</td><td>{artifact}</td></tr>".format(
cohort=html.escape(cohort), run=html.escape(str(run.get("runId"))), mode=html.escape(str(run.get("syncMode"))), start=html.escape(str(run.get("actualStartRfc3339Utc"))), wall=number(run.get("wallMs"), 1), rss=number(run.get("maxRssKb")), lag=number(run.get("scheduleLagMs"), 1),
vrp=number(run.get("vrps")), vap=number(run.get("vaps")), pp=number(run.get("publicationPoints")), warnings=number(run.get("warnings")), artifact="complete" if run.get("artifactsComplete") and not run.get("missingArtifacts") else "INCOMPLETE",
)
for cohort, run in run_rows(ordered)
)
evidence_rows_html = "".join(
"<tr><td>{cohort}</td><td><code>{root}</code></td><td><code>{summary}</code></td></tr>".format(
cohort=html.escape(str(record.get("cohortId"))),
root=html.escape(str(record.get("packageRoot", "n/a"))),
summary=html.escape(f"{record.get('packageRoot', 'n/a')}/experiments/feature149-{record.get('cohortId')}/cohort-summary.json"),
)
for record in ordered
)
warning_values = [latest(record, "warnings") for record in ordered if isinstance(latest(record, "warnings"), (int, float))]
max_delta = max((run.get("wallMs", 0) for _, run in run_rows(ordered) if run.get("syncMode") == "delta"), default=0)
report_html = f'''<!doctype html><html lang="zh-CN"><meta charset="utf-8"><title>Feature #149 性能实验报告</title>
<style>
body{{font-family:Inter,system-ui,sans-serif;margin:0;background:#f8fafc;color:#0f172a}}main{{max-width:1380px;margin:auto;padding:34px}}h1{{margin-bottom:4px}}.sub{{color:#475569}}.cards{{display:grid;grid-template-columns:repeat(4,1fr);gap:14px;margin:26px 0}}.card{{background:white;border:1px solid #e2e8f0;border-radius:12px;padding:16px}}.card strong{{display:block;font-size:25px;margin:8px 0}}.card small{{color:#64748b}}section{{background:white;border:1px solid #e2e8f0;border-radius:12px;padding:20px;margin-top:18px;overflow:auto}}table{{border-collapse:collapse;width:100%;font-size:13px}}th,td{{padding:9px;border-bottom:1px solid #e2e8f0;text-align:left;white-space:nowrap}}th{{background:#f1f5f9}}svg{{width:100%;height:auto;min-width:760px}}.axis,.label{{font-size:12px;fill:#475569}}.value{{font-size:13px;font-weight:700;fill:#0f172a}}.circle-label{{font-size:10px;fill:#fff;font-weight:700}}.note{{color:#475569;line-height:1.6}}li{{margin:7px 0;line-height:1.5}}code{{background:#f1f5f9;padding:2px 5px;border-radius:4px}}
</style>
<main><h1>Feature #149系统盘 / 数据盘缓存性能实验</h1><p class="sub">远端 {html.escape(args.remote_host)} · source {html.escape(args.source_commit)} · archive SHA-256 {html.escape(args.package_sha256)} · 4 cohorts / 24 serial all5 runs</p><div class="cards">{card_html}</div>
<section><h2>实验拓扑与时序</h2><p class="note">amd64 远端主机的 system cohort portable packagestate数据和日志全部写在系统盘data cohort 将对应内容全部写在 <code>/data</code>四个 cohort A-system A-data B-system B-data 串行执行每个 row 1 snapshot + 5 delta相邻启动节拍 600 </p>{timeline_svg(ordered)}</section>
<section><h2>Milestone timeline</h2>{milestone_svg()}<p class="note">M1M5 均已通过磁盘初始化 checksum package 部署与 dry-runA/B 两组正式运行证据归档和报告收口</p></section>
<section><h2>主机磁盘与 provenance</h2><p class="note"><code>{html.escape(args.remote_host)}</code>system 为远端根文件系统/dev/vda3data /data/dev/vdb1ext4rpki-data同一 archive checksum <code>{html.escape(args.package_sha256)}</code>源码 commit <code>{html.escape(args.source_commit)}</code>对象 cache 固定包含 ROA child-certificate validation cache profile 的唯一 cache 差异是 transport prefetch</p></section>
<section><h2>结论摘要</h2><ul>{''.join(f'<li>{html.escape(line)}</li>' for line in conclusion_lines(indexed))}</ul></section>
<section><h2>Delta median wall clock</h2>{svg_chart(ordered)}<p class="note">颜色蓝色 system青绿色 data全体 delta median {number(all_stats.get('median'), 1)} ms最大 delta {number(max_delta, 1)} ms长尾包含网络同步窗口</p></section>
<section><h2> cohort KPI</h2><table><tr><th>cohort</th><th>disk</th><th>profile</th><th>elapsed</th><th>snapshot</th><th>delta min/mean/median/p90/max</th><th>stable median</th><th>max RSS</th><th>VRP</th><th>VAP</th><th>PP</th><th>warnings</th></tr>{cohort_rows_html}</table></section>
<section><h2>磁盘配对all delta / stable delta median</h2><table><tr><th>profile</th><th>system ms</th><th>data ms</th><th>data vs systemall / stable</th></tr>{paired_html}</table><p class="note">负值表示 data median 更快正值表示更慢snapshot 单样本另行列在 cohort KPI 表中</p></section>
<section><h2>磁盘配对all delta / stable delta mean</h2><table><tr><th>profile</th><th>system ms</th><th>data ms</th><th>data vs systemall / stable</th></tr>{paired_mean_html}</table><p class="note">这里的 mean 是对应 cohort deltaWallMs 平均值负值表示 data mean 更快</p></section>
<section><h2>Prefetch 开关对比stable delta median</h2><table><tr><th>disk</th><th>no prefetch ms</th><th>prefetch ms</th><th>prefetch vs no prefetch</th></tr>{prefetch_html}</table></section>
<section><h2>Prefetch 开关对比stable delta mean</h2><table><tr><th>disk</th><th>no prefetch ms</th><th>prefetch ms</th><th>prefetch vs no prefetch</th></tr>{prefetch_mean_html}</table></section>
<section><h2> run 原始指标</h2><table><tr><th>cohort</th><th>run</th><th>mode</th><th>actual start UTC</th><th>wall ms</th><th>max RSS KiB</th><th>schedule lag ms</th><th>VRP/VAP/PP/warnings</th><th>artifacts</th></tr>{run_rows_html}</table></section>
<section><h2>验收与异常诊断</h2><ul><li>4 cohort 均为 6/6 success首轮 snapshot 后连续五轮 deltasummary 中每 run 的核心产物均完整实际启动间隔校验为 600 </li><li>最新 warnings 范围为 {number(min(warning_values) if warning_values else None)}{number(max(warning_values) if warning_values else None)}VRP/VAP/PP live 窗口内小幅变化未出现输出塌缩或 recovery snapshot</li><li>结果受 live RPKI 发布变化RRDP/rsync 网络长尾和顺序时间窗口影响不能仅凭四组 wall 值声称 IOPS 的严格因果效应</li></ul><table><tr><th>cohort</th><th>远端 package/run root</th><th>远端 cohort summary</th></tr>{evidence_rows_html}</table><p class="note">本地输入证据为{'; '.join(f'<code>{html.escape(str(path))}</code>' for path in input_paths)}</p></section>
<section><h2>统计口径</h2><p class="note">snapshot 统计只包含每个 cohort 的首轮all delta 统计包含 delta1delta5 20 个样本stable delta 统计包含 delta2delta5 16 个样本详细 cache 命中stage timing命令 argvrun-meta/run-summary 和完整产物仍在远端 run root</p></section></main></html>'''
args.out_html.parent.mkdir(parents=True, exist_ok=True)
args.out_markdown.parent.mkdir(parents=True, exist_ok=True)
args.out_html.write_text(report_html, encoding="utf-8")
write_markdown(ordered, args.source_commit, args.package_sha256, args.remote_host, input_paths, args.out_markdown)
if __name__ == "__main__":
main()

View File

@ -38,7 +38,8 @@ Environment:
EXPERIMENT_RUN_ROOT shared run root/state root; default PACKAGE_ROOT EXPERIMENT_RUN_ROOT shared run root/state root; default PACKAGE_ROOT
EXPERIMENT_DIR experiment metadata output directory EXPERIMENT_DIR experiment metadata output directory
CASE_RUNS delta runs per case; default 10 CASE_RUNS delta runs per case; default 10
EXPERIMENT_CASE_SET default, cache-only, crypto-sig or sig-pp-compare; default runs the original 4-case matrix EXPERIMENT_CASE_SET default, cache-only, crypto-sig, sig-pp-compare,
feature149-prefetch or feature149-no-prefetch
RUN_START_INTERVAL_SECS fixed start cadence for all runs; default 600 RUN_START_INTERVAL_SECS fixed start cadence for all runs; default 600
FIRST_RUN_DELAY_SECS delay before the first scheduled run; default 0 FIRST_RUN_DELAY_SECS delay before the first scheduled run; default 0
SNAPSHOT_EXTRA_ARGS extra rpki args for snapshot warmup SNAPSHOT_EXTRA_ARGS extra rpki args for snapshot warmup
@ -98,7 +99,8 @@ case_count() {
crypto-sig) printf '%s' 4 ;; crypto-sig) printf '%s' 4 ;;
sig-pp-compare) printf '%s' 2 ;; sig-pp-compare) printf '%s' 2 ;;
baseline-combo) printf '%s' 2 ;; baseline-combo) printf '%s' 2 ;;
*) die "EXPERIMENT_CASE_SET must be default, cache-only, crypto-sig or sig-pp-compare: $EXPERIMENT_CASE_SET" ;; feature149-prefetch|feature149-no-prefetch) printf '%s' 1 ;;
*) die "unknown EXPERIMENT_CASE_SET: $EXPERIMENT_CASE_SET" ;;
esac esac
} }
@ -119,6 +121,8 @@ case_id_for_index() {
sig-pp-compare:2) printf '%s' "pp-only" ;; sig-pp-compare:2) printf '%s' "pp-only" ;;
baseline-combo:1) printf '%s' "baseline" ;; baseline-combo:1) printf '%s' "baseline" ;;
baseline-combo:2) printf '%s' "pp-object-sig" ;; baseline-combo:2) printf '%s' "pp-object-sig" ;;
feature149-prefetch:1) printf '%s' "prefetch-pp-object" ;;
feature149-no-prefetch:1) printf '%s' "pp-object" ;;
*) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;; *) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;;
esac esac
} }
@ -140,6 +144,8 @@ case_name_for_index() {
sig-pp-compare:2) printf '%s' "pp-cache-only" ;; sig-pp-compare:2) printf '%s' "pp-cache-only" ;;
baseline-combo:1) printf '%s' "all-cache-off" ;; baseline-combo:1) printf '%s' "all-cache-off" ;;
baseline-combo:2) printf '%s' "pp-cache-object-crypto-sig-cache" ;; baseline-combo:2) printf '%s' "pp-cache-object-crypto-sig-cache" ;;
feature149-prefetch:1) printf '%s' "prefetch-pp-object-cache" ;;
feature149-no-prefetch:1) printf '%s' "pp-object-cache" ;;
*) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;; *) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;;
esac esac
} }
@ -161,6 +167,8 @@ case_extra_args_for_index() {
sig-pp-compare:2) printf '%s' "--enable-publication-point-validation-cache" ;; sig-pp-compare:2) printf '%s' "--enable-publication-point-validation-cache" ;;
baseline-combo:1) printf '%s' "" ;; baseline-combo:1) printf '%s' "" ;;
baseline-combo:2) printf '%s' "--enable-publication-point-validation-cache --enable-roa-validation-cache --enable-crypto-signature-cache" ;; baseline-combo:2) printf '%s' "--enable-publication-point-validation-cache --enable-roa-validation-cache --enable-crypto-signature-cache" ;;
feature149-prefetch:1) printf '%s' "--enable-transport-request-prefetch --enable-publication-point-validation-cache --enable-roa-validation-cache --parallel-max-repo-sync-workers-global 4 --parallel-phase2-object-workers 4 --memory-trim-after-validation" ;;
feature149-no-prefetch:1) printf '%s' "--enable-publication-point-validation-cache --enable-roa-validation-cache --parallel-max-repo-sync-workers-global 4 --parallel-phase2-object-workers 4 --memory-trim-after-validation" ;;
*) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;; *) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;;
esac esac
} }
@ -168,6 +176,7 @@ case_extra_args_for_index() {
case_child_cert_cache_for_index() { case_child_cert_cache_for_index() {
case "$EXPERIMENT_CASE_SET:$1" in case "$EXPERIMENT_CASE_SET:$1" in
default:4|cache-only:2|cache-only:3|crypto-sig:3|crypto-sig:4|baseline-combo:2) printf '%s' "1" ;; default:4|cache-only:2|cache-only:3|crypto-sig:3|crypto-sig:4|baseline-combo:2) printf '%s' "1" ;;
feature149-prefetch:1|feature149-no-prefetch:1) printf '%s' "1" ;;
default:1|default:2|default:3|cache-only:1|crypto-sig:1|crypto-sig:2|sig-pp-compare:1|sig-pp-compare:2|baseline-combo:1) printf '%s' "0" ;; default:1|default:2|default:3|cache-only:1|crypto-sig:1|crypto-sig:2|sig-pp-compare:1|sig-pp-compare:2|baseline-combo:1) printf '%s' "0" ;;
*) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;; *) die "unknown case index: $1 for set $EXPERIMENT_CASE_SET" ;;
esac esac
@ -207,6 +216,14 @@ elif case_set == "baseline-combo":
{"caseId": "baseline", "caseName": "all-cache-off", "extraArgs": "", "enableChildCertificateValidationCache": False}, {"caseId": "baseline", "caseName": "all-cache-off", "extraArgs": "", "enableChildCertificateValidationCache": False},
{"caseId": "pp-object-sig", "caseName": "pp-cache-object-crypto-sig-cache", "extraArgs": "--enable-publication-point-validation-cache --enable-roa-validation-cache --enable-crypto-signature-cache", "enableChildCertificateValidationCache": True}, {"caseId": "pp-object-sig", "caseName": "pp-cache-object-crypto-sig-cache", "extraArgs": "--enable-publication-point-validation-cache --enable-roa-validation-cache --enable-crypto-signature-cache", "enableChildCertificateValidationCache": True},
] ]
elif case_set == "feature149-prefetch":
cases = [
{"caseId": "prefetch-pp-object", "caseName": "prefetch-pp-object-cache", "extraArgs": "--enable-transport-request-prefetch --enable-publication-point-validation-cache --enable-roa-validation-cache --parallel-max-repo-sync-workers-global 4 --parallel-phase2-object-workers 4 --memory-trim-after-validation", "enableChildCertificateValidationCache": True},
]
elif case_set == "feature149-no-prefetch":
cases = [
{"caseId": "pp-object", "caseName": "pp-object-cache", "extraArgs": "--enable-publication-point-validation-cache --enable-roa-validation-cache --parallel-max-repo-sync-workers-global 4 --parallel-phase2-object-workers 4 --memory-trim-after-validation", "enableChildCertificateValidationCache": True},
]
else: else:
raise SystemExit(f"unknown case set: {case_set}") raise SystemExit(f"unknown case set: {case_set}")
print(json.dumps(cases, ensure_ascii=False, indent=8)) print(json.dumps(cases, ensure_ascii=False, indent=8))

View File

@ -0,0 +1,79 @@
#!/usr/bin/env bash
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
PACKAGE_ROOT="${PACKAGE_ROOT:-$(cd "$SCRIPT_DIR/../.." && pwd)}"
COHORT_ID="${COHORT_ID:?COHORT_ID is required}"
COHORT_DISK="${COHORT_DISK:?COHORT_DISK is required (system or data)}"
COHORT_PROFILE="${COHORT_PROFILE:?COHORT_PROFILE is required (prefetch-pp-object or pp-object)}"
RUN_START_INTERVAL_SECS="${RUN_START_INTERVAL_SECS:-600}"
CASE_RUNS="${CASE_RUNS:-5}"
DRY_RUN="${DRY_RUN:-0}"
FIRST_RUN_NOT_BEFORE_EPOCH="${FIRST_RUN_NOT_BEFORE_EPOCH:-0}"
die() {
echo "error: $*" >&2
exit 2
}
is_true() {
case "${1:-}" in
1|true|TRUE|yes|YES|on|ON) return 0 ;;
*) return 1 ;;
esac
}
case "$COHORT_DISK" in
system|data) ;;
*) die "COHORT_DISK must be system or data: $COHORT_DISK" ;;
esac
case "$COHORT_PROFILE" in
prefetch-pp-object) case_set="feature149-prefetch" ;;
pp-object) case_set="feature149-no-prefetch" ;;
*) die "COHORT_PROFILE must be prefetch-pp-object or pp-object: $COHORT_PROFILE" ;;
esac
[[ "$CASE_RUNS" == "5" ]] || die "Feature #149 requires CASE_RUNS=5, got $CASE_RUNS"
[[ "$RUN_START_INTERVAL_SECS" == "600" ]] || die "Feature #149 requires RUN_START_INTERVAL_SECS=600, got $RUN_START_INTERVAL_SECS"
[[ -x "$SCRIPT_DIR/run_cache_ablation_experiment.sh" ]] || die "missing cache ablation driver"
[[ -x "$SCRIPT_DIR/summarize_feature149_cohort.py" ]] || die "missing Feature #149 summarizer"
[[ -f "$PACKAGE_ROOT/.env" ]] || die "missing package environment: $PACKAGE_ROOT/.env"
experiment_dir="$PACKAGE_ROOT/experiments/feature149-$COHORT_ID"
summary_jsonl="$experiment_dir/experiment-summary.jsonl"
if (( FIRST_RUN_NOT_BEFORE_EPOCH > 0 )) && ! is_true "$DRY_RUN"; then
now_epoch="$(date +%s)"
if (( now_epoch < FIRST_RUN_NOT_BEFORE_EPOCH )); then
wait_secs=$(( FIRST_RUN_NOT_BEFORE_EPOCH - now_epoch ))
echo "[$(date -u +%Y-%m-%dT%H:%M:%SZ)] waiting ${wait_secs}s before cohort=$COHORT_ID" >&2
sleep "$wait_secs"
fi
fi
env \
PACKAGE_ROOT="$PACKAGE_ROOT" \
ENV_FILE="$PACKAGE_ROOT/.env" \
EXPERIMENT_RUN_ROOT="$PACKAGE_ROOT" \
EXPERIMENT_DIR="$experiment_dir" \
EXPERIMENT_CASE_SET="$case_set" \
CASE_RUNS="$CASE_RUNS" \
RUN_SNAPSHOT=1 \
RUN_START_INTERVAL_SECS="$RUN_START_INTERVAL_SECS" \
FIRST_RUN_DELAY_SECS=0 \
RETAIN_RUNS=6 \
DRY_RUN="$DRY_RUN" \
"$SCRIPT_DIR/run_cache_ablation_experiment.sh"
if ! is_true "$DRY_RUN"; then
"$SCRIPT_DIR/summarize_feature149_cohort.py" \
--cohort-id "$COHORT_ID" \
--cohort-disk "$COHORT_DISK" \
--cohort-profile "$COHORT_PROFILE" \
--package-root "$PACKAGE_ROOT" \
--summary-jsonl "$summary_jsonl" \
--out-dir "$experiment_dir"
fi
printf 'feature149_cohort_dir=%s\n' "$experiment_dir"

View File

@ -0,0 +1,169 @@
#!/usr/bin/env python3
"""Validate and summarize one Feature #149 six-run cohort."""
from __future__ import annotations
import argparse
import json
import statistics
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
REQUIRED_ARTIFACTS = {
"run-meta.json",
"run-summary.json",
"input.cir",
"result.ccr",
"report.json",
"vrps.csv",
"vaps.csv",
"stage-timing.json",
"process-time.txt",
}
def load_jsonl(path: Path) -> list[dict[str, Any]]:
records: list[dict[str, Any]] = []
for line_number, line in enumerate(path.read_text(encoding="utf-8").splitlines(), 1):
if line.strip():
value = json.loads(line)
if not isinstance(value, dict):
raise ValueError(f"{path}:{line_number} is not an object")
records.append(value)
return records
def require_success(records: list[dict[str, Any]], package_root: Path) -> list[dict[str, Any]]:
if len(records) != 6:
raise ValueError(f"expected 6 records (snapshot + 5 delta), found {len(records)}")
for index, record in enumerate(records):
expected_mode = "snapshot" if index == 0 else "delta"
if record.get("status") != "success":
raise ValueError(f"run {index + 1} status is {record.get('status')!r}")
if record.get("syncMode") != expected_mode:
raise ValueError(
f"run {index + 1} syncMode is {record.get('syncMode')!r}, expected {expected_mode!r}"
)
run_dir = package_root / "runs" / f"run_{int(record['maxRunIndexAfter']):04d}"
missing = sorted(name for name in REQUIRED_ARTIFACTS if not (run_dir / name).is_file())
record["runDir"] = str(run_dir)
record["artifactsComplete"] = not missing
record["missingArtifacts"] = missing
if missing:
raise ValueError(f"run {index + 1} missing required artifacts: {', '.join(missing)}")
return records
def percentile(values: list[float], fraction: float) -> float | None:
if not values:
return None
ordered = sorted(values)
position = (len(ordered) - 1) * fraction
lower = int(position)
upper = min(lower + 1, len(ordered) - 1)
return ordered[lower] + (ordered[upper] - ordered[lower]) * (position - lower)
def stats(values: list[int | float | None]) -> dict[str, float | None]:
nums = [float(value) for value in values if isinstance(value, (int, float))]
if not nums:
return {"count": 0, "min": None, "median": None, "p90": None, "max": None, "mean": None}
return {
"count": len(nums),
"min": min(nums),
"median": statistics.median(nums),
"p90": percentile(nums, 0.9),
"max": max(nums),
"mean": statistics.fmean(nums),
}
def iso(epoch: Any) -> str | None:
if not isinstance(epoch, (int, float)):
return None
return datetime.fromtimestamp(epoch, timezone.utc).isoformat().replace("+00:00", "Z")
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--cohort-id", required=True)
parser.add_argument("--cohort-disk", required=True, choices=("system", "data"))
parser.add_argument("--cohort-profile", required=True, choices=("prefetch-pp-object", "pp-object"))
parser.add_argument("--package-root", required=True, type=Path)
parser.add_argument("--summary-jsonl", required=True, type=Path)
parser.add_argument("--out-dir", required=True, type=Path)
args = parser.parse_args()
records = require_success(load_jsonl(args.summary_jsonl), args.package_root)
delta = records[1:]
elapsed_seconds = records[-1]["completedEpoch"] - records[0]["actualStartEpoch"]
report = {
"feature": "149",
"createdAtUtc": datetime.now(timezone.utc).isoformat().replace("+00:00", "Z"),
"cohortId": args.cohort_id,
"disk": args.cohort_disk,
"profile": args.cohort_profile,
"packageRoot": str(args.package_root),
"runCount": len(records),
"successCount": len(records),
"artifactStatus": "complete",
"elapsedSeconds": elapsed_seconds,
"actualStartedAtUtc": iso(records[0].get("actualStartEpoch")),
"completedAtUtc": iso(records[-1].get("completedEpoch")),
"maxRssKb": max(int(record["maxRssKb"]) for record in records if isinstance(record.get("maxRssKb"), (int, float))),
"snapshot": {"wallMs": records[0].get("wallMs"), "maxRssKb": records[0].get("maxRssKb")},
"deltaWallMs": stats([record.get("wallMs") for record in delta]),
"stableDeltaWallMs": stats([record.get("wallMs") for record in delta[1:]]),
"latestCounts": {
key: records[-1].get(key)
for key in ("vrps", "vaps", "publicationPoints", "warnings")
},
"runs": records,
}
args.out_dir.mkdir(parents=True, exist_ok=True)
json_path = args.out_dir / "cohort-summary.json"
markdown_path = args.out_dir / "cohort-summary.md"
json_path.write_text(json.dumps(report, ensure_ascii=False, indent=2, sort_keys=True) + "\n", encoding="utf-8")
latest = report["latestCounts"]
markdown_path.write_text(
"\n".join(
[
f"# Feature #149 cohort: {args.cohort_id}",
"",
f"- 磁盘:`{args.cohort_disk}`",
f"- profile`{args.cohort_profile}`",
f"- 状态:`success`6/6 run 成功,必要产物完整",
f"- 总执行耗时:`{elapsed_seconds}s`",
f"- 最高 RSS`{report['maxRssKb']} KiB`",
f"- snapshot wall`{records[0].get('wallMs')} ms`",
f"- delta median / p90`{report['deltaWallMs']['median']} ms` / `{report['deltaWallMs']['p90']} ms`",
f"- 最新产物VRP `{latest['vrps']}`、VAP `{latest['vaps']}`、PP `{latest['publicationPoints']}`、warnings `{latest['warnings']}`",
"",
"| run | mode | wall ms | max RSS KiB | VRP | VAP | PP | warnings | artifacts |",
"| --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | --- |",
*[
"| {run} | {mode} | {wall} | {rss} | {vrps} | {vaps} | {pps} | {warnings} | {artifacts} |".format(
run=index + 1,
mode=record.get("syncMode"),
wall=record.get("wallMs"),
rss=record.get("maxRssKb"),
vrps=record.get("vrps"),
vaps=record.get("vaps"),
pps=record.get("publicationPoints"),
warnings=record.get("warnings"),
artifacts="complete" if record.get("artifactsComplete") else "missing",
)
for index, record in enumerate(records)
],
"",
]
),
encoding="utf-8",
)
print(json.dumps({"cohortSummaryJson": str(json_path), "cohortSummaryMarkdown": str(markdown_path), "elapsedSeconds": elapsed_seconds, "maxRssKb": report["maxRssKb"]}, ensure_ascii=False))
if __name__ == "__main__":
main()